Scatter3d plot#
The scatter3d plot creates a three-dimensional scatter plot of the data.
[1]:
import plopp as pp
import scipp as sc
import numpy as np
Scatter plot using a positions vector#
The easiest way to generate a scatter plot is to use a coordinate of the data array that contains data of the vector3 dtype.
We first generate some fake data, meant to represent clusters of points in a three-dimensional space.
[2]:
nclusters = 100
npercluster = 1000
position = np.zeros((nclusters, npercluster, 3))
values = np.zeros((nclusters, npercluster))
for n in range(nclusters):
center = 500.0 * (np.random.random(3) - 0.5)
r = 20.0 * np.random.normal(size=[npercluster, 3])
position[n, :] = r + center
values[n, :] = np.linalg.norm(r, axis=1) + n
da = sc.DataArray(
data=sc.array(dims=['row'], values=values.flatten(), unit='K'),
coords={
'position': sc.vectors(
dims=['row'], unit='m', values=position.reshape(nclusters * npercluster, 3)
)
},
)
da
[2]:
scipp.DataArray (3.05 MB)
- row: 100000
- position(row)vector3m[ -16.74135067 -188.12056179 -32.76375867], [ -52.65398174 -182.54806198 -93.87922006], ..., [-240.1528684 -38.0334395 -179.03587494], [-236.37264552 13.70327652 -117.61870302]
Values:
array([[ -16.74135067, -188.12056179, -32.76375867], [ -52.65398174, -182.54806198, -93.87922006], [ -15.16606557, -224.26898961, -31.42662984], ..., [-214.56094981, 19.61559158, -143.2142371 ], [-240.1528684 , -38.0334395 , -179.03587494], [-236.37264552, 13.70327652, -117.61870302]], shape=(100000, 3))
- (row)float64K49.745, 46.595, ..., 145.128, 137.333
Values:
array([ 49.74457703, 46.59514144, 44.40847174, ..., 127.07263384, 145.1280956 , 137.33300056], shape=(100000,))
We then simply specify the name of the coordinate that contains the vector positions using the pos argument:
[3]:
pp.scatter3d(da, pos='position', color='black', size=2)
[3]:
Scatter plot with colorbar#
To make a scatter plot with a colorbar mapping data values to colors, use cbar=True.
[4]:
pp.scatter3d(da, pos='position', cbar=True, size=2)
[4]:
Scatter plot using individual coordinates#
It is also possible to create scatter plots using three individual coordinate names for the x, y, z dimensions:
[5]:
time = np.linspace(0, 10, 50)
x = np.cos(time)
y = np.sin(time)
da = sc.DataArray(
data=sc.array(dims=['row'], values=time),
coords={
'x': sc.array(dims=['row'], unit='m', values=x),
'y': sc.array(dims=['row'], unit='m', values=y),
'time': sc.array(dims=['row'], unit='s', values=time),
},
)
pp.scatter3d(da, x='x', y='y', z='time', size=0.2, cbar=True)
[5]: